code: def __init__(
      self,
      video_modality_dim,
      text_dim,
      audio_cluster=8,
      text_cluster=32,
  ):
      super(Net, self).__init__()
  
      self.audio_pooling = NetVLAD(
          feature_size=video_modality_dim["audio"][1],
          cluster_size=audio_cluster,
      )
      self.text_pooling = NetVLAD(
          feature_size=text_dim, cluster_size=text_cluster
      )
  
      self.mee = MEE(video_modality_dim, self.text_pooling.out_dim)
  
imports: from torch.autograd import Variable
  import torch.nn
  import torch.nn.functional
  import torch
  from loupe import NetVLAD
  import numpy
  from torch.autograd import Function
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: nn with example: obj = Net(video_modality_dim, text_dim, audio_cluster, text_cluster)